Please use this identifier to cite or link to this item:
http://hdl.handle.net/11375/30135
Title: | Model-Based Fault Detection of a Battery System in a Hybrid Electric Vehicle |
Authors: | Gadsden SA Habibi SR |
Department: | Mechanical Engineering |
Keywords: | 4007 Control Engineering, Mechatronics and Robotics;40 Engineering;4010 Engineering Practice and Education;7 Affordable and Clean Energy |
Publication Date: | 1-Sep-2011 |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Abstract: | Recently, a new type of interacting multiple model (IMM) method was introduced based on the relatively new smooth variable structure filter (SVSF), and is referred to as the IMM-SVSF. The SVSF is a type of sliding mode estimator that is formulated in a predictor-corrector fashion. This strategy keeps the estimated state bounded within a region of the true state trajectory, thus creating a stable and robust estimation process. The IMM method may be utilized for fault detection and diagnosis, and is classified as a model-based method. In this paper, for the purposes of fault detection, the IMM-SVSF is applied through simulation on a simple battery system which is modeled from a hybrid electric vehicle. © 2011 IEEE. |
metadata.dc.rights.license: | Attribution-NonCommercial-NoDerivs - CC BY-NC-ND |
URI: | http://hdl.handle.net/11375/30135 |
metadata.dc.identifier.doi: | https://doi.org/10.1109/vppc.2011.6043175 |
Appears in Collections: | Mechanical Engineering Publications |
Files in This Item:
File | Description | Size | Format | |
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006-562737dcb6c58.pdf | 542.8 kB | Adobe PDF | View/Open |
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